Data visualization basics

Originally published on Africa Check, a non-profit fact-checking organization; @AfricaCheck.

Sometimes data can tell a story more effectively than words or photos. Once you’ve researched and come up with a great data-driven story, you’ll need to present it. This usually involves visualizing the data you’re working with. Here is a guide that briefly explains some easy-to-use tools to help you get started.

To visualize or not?

The first question you should always ask yourself is whether visualizing your data is really necessary. Would it make the story easier to understand? Does it provide context? Is it relevant?

Including a visualization just for the sake of it can be confusing and reduce the impact of your story. Remember that bad data visualizationcan be worse than none at all.

When to use what

It’s important to choose the right kind of graph to visualize your data. Below is a brief summary of various types of graphs and when it’s best to use what.

Bar charts

Bar charts (or column charts) are great for making comparisons between two or more things. They can also be used to show change over time, but they can be difficult to read if the changes are small.

Line charts

These are best for showing change over time, particularly if the changes are fairly small and would not be as easy to see if you used a bar chart.

Pie charts

Pie charts are often misused and some people feel they should not be used at all. A bar chart is a far more understandable way of presenting your data on most occasions. (It’s easier for the human eye to compare the heights of columns than the area of a pie chart.)

However, pie charts are very good for showing parts of a whole. Avoid using pie charts when you have more than two values.

Area charts

These are good for showing total change over time when there are several categories or values contributing to a total, for example, if you wanted to show changes in the performance of four different sectors of the economy and of the economy overall, over time.

Scatter charts

Scatter graphs, or XY plots, are great for showing relationships or correlations between things. They are also a great way to spot outliers in data.

Treemaps

Treemaps are a great way to compare things that are in a hierarchy and show the ratios of components.

General tips for creating graphs or charts

Make sure everything is clearly labeled. If people don’t know what is being represented they won’t be able to understand your data.

Use a legend if necessary. If you’ve used colors or symbols in your visualization make sure people know what they represent.

Specify units. Simply having a value of 10 is meaningless unless you know if it’s 10 meters, 10 millimeters or 10 years.

Always start your axis at 0 and use even intervals. Starting at another value or using uneven intervals can make graphs misleading.

Avoid 3-D and ‘blow-apart’ effects. As tempting as it is and as nice as you might think it looks, this makes it very difficult to visually compare data. A good example of misleading 3-D charts can be found here.

Less is more. Make your visualizations as simple and clean as possible, it makes them much easier to understand and usually more visually appealing. Keep the ‘data to ink ratio’ in mind – if you had to print your visualization try and show as much information as possible using the least ink.